Exemplo n.º 1
0
    def _plot_default(self):
        # Create the plot
        index_mapper = LinearMapper(range=DataRange1D(low=0, high=0.0012))
        value_mapper = LinearMapper(range=DataRange1D(low=-0.00025, high=0.00025))
        plot = SnippetChannelPlot(history=20,
                source=self.channels[self.channel-1],
                value_mapper=value_mapper, 
                index_mapper=index_mapper,
                bgcolor='white', padding=[60, 5, 5, 20])
        add_default_grids(plot, major_index=1e-3, minor_index=1e-4,
                major_value=1e-3, minor_value=1e-4)

        # Add the axes labels
        axis = PlotAxis(orientation='left', component=plot,
                tick_label_formatter=scale_formatter, title='Signal (mV)')
        plot.overlays.append(axis)
        axis = PlotAxis(orientation='bottom', component=plot, 
                tick_label_formatter=scale_formatter)
        plot.overlays.append(axis)

        # Add the tools
        zoom = ZoomTool(plot, drag_button=None, axis="value")
        plot.overlays.append(zoom)
        self.tool = WindowTool(component=plot)
        plot.overlays.append(self.tool)
        
        # Whenever we draw a window, the settings should immediately be updated!
        self.sync_trait('windows', self.tool)
        return plot
Exemplo n.º 2
0
    def _add_default_axes_and_grids(self, plot, value):
        value_trait = self.data.trait(value)
        axis = PlotAxis(plot, orientation='left', title=value_trait.label)
        plot.overlays.append(axis)
        
        index_title = self.paradigm.get_parameter_label(self.data.parameters[-1])
        axis = PlotAxis(plot, orientation='bottom', title=index_title)
        plot.overlays.append(axis)

        minor, major = value_trait.suggested_grid
        add_default_grids(plot, minor_value=minor, major_value=major)
 def _update_experiment_plot(self):
     index_range = ChannelDataRange(trig_delay=0)
     index_range.sources = [self.data.contact_digital]
     index_mapper = LinearMapper(range=index_range)
     container = OverlayPlotContainer(padding=[20, 20, 50, 5])
     self._add_experiment_plots(index_mapper, container)
     # Add axes and grids to the first plot
     plot = container.components[0]
     add_default_grids(plot, minor_index=0.25, major_index=1)
     add_time_axis(plot, orientation='top')
     self.experiment_plot = container
 def _generate_experiment_plot(self):
     index_range = ChannelDataRange(trig_delay=0)
     index_range.sources = [self.data.spout_TTL]
     index_mapper = LinearMapper(range=index_range)
     self.index_range = index_range
     container = OverlayPlotContainer(padding=[20, 20, 50, 5])
     self._add_experiment_plots(index_mapper, container, 0.5)
     plot = container.components[0]
     add_default_grids(plot, major_index=1, minor_index=0.25)
     add_time_axis(plot, orientation='top')
     self.experiment_plot = container
    def _data_changed(self):
        index_range = ChannelDataRange(trig_delay=0)
        index_range.add(self.data.spout_TTL)
        index_mapper = LinearMapper(range=index_range)
        value_range = DataRange1D(low_setting=-0, high_setting=1)
        value_mapper = LinearMapper(range=value_range)
        container = OverlayPlotContainer(bgcolor='white', fill_padding=True,
                padding=50, spacing=50)

        # SIGNAL
        plot = TTLPlot(source=self.data.signal_TTL,
                index_mapper=index_mapper, value_mapper=value_mapper,
                fill_color=(0, 1, 0, 0.5), rect_height=0.2, rect_center=0.9)
        container.add(plot)

        # PUMP
        plot = TTLPlot(source=self.data.pump_TTL,
                index_mapper=index_mapper, value_mapper=value_mapper,
                fill_color=(0, 0, 1, 0.5), rect_height=0.2, rect_center=0.7)
        container.add(plot)

        # SPOUT
        plot = TTLPlot(source=self.data.spout_TTL, reference=0,
                index_mapper=index_mapper, value_mapper=value_mapper,
                fill_color=(1, 1, 1, 0.5), rect_height=0.2, rect_center=0.5)
        container.add(plot)

        # OVERRIDE
        plot = TTLPlot(source=self.data.override_TTL, reference=0,
                index_mapper=index_mapper, value_mapper=value_mapper,
                fill_color=(1, 0, 0, 0.5), rect_height=0.2, rect_center=0.3)
        container.add(plot)

        # FREE RUN
        plot = TTLPlot(source=self.data.free_run_TTL, reference=0,
                index_mapper=index_mapper, value_mapper=value_mapper,
                fill_color=(1, 0, 0, 0.5), rect_height=0.2, rect_center=0.1)
        container.add(plot)

        # Add the axes and grids
        grid = PlotGrid(mapper=plot.index_mapper, component=plot,
                orientation='vertical', line_color='lightgray',
                line_style='dot', grid_interval=0.25)
        plot.underlays.append(grid)
        grid = PlotGrid(mapper=plot.index_mapper, component=plot,
                orientation='vertical', line_color='lightgray',
                line_style='solid', grid_interval=1)
        plot.underlays.append(grid)

        add_time_axis(plot)
        add_default_grids(plot, major_index=1, minor_index=0.25)

        # set up microphone plot
        value_range = DataRange1D(low_setting=0, high_setting=80)
        value_mapper = LinearMapper(range=value_range)
        plot = RMSChannelPlot(source=self.data.microphone,
                index_mapper=index_mapper, value_mapper=value_mapper,
                line_color=(0, 0, 0, 0.25))
        self.microphone_plot = plot
        container.add(plot)

        self.contact_plot = container
Exemplo n.º 6
0
    def _generate_physiology_plot(self):
        # NOTE THAT ORDER IS IMPORTANT.  First plots added are at bottom of
        # z-stack, so the physiology must be last so it appears on top.

        # Padding is in left, right, top, bottom order
        container = OverlayPlotContainer(padding=[50, 20, 20, 50])

        # Create the index range shared by all the plot components
        self.physiology_index_range = ChannelDataRange(span=5, trig_delay=1,
                timeseries=self.data.ts, sources=[self.data.processed])

        # Create the TTL plot
        index_mapper = LinearMapper(range=self.physiology_index_range)
        value_mapper = LinearMapper(range=DataRange1D(low=0, high=1))
        plot = TTLPlot(source=self.data.sweep,
                index_mapper=index_mapper, value_mapper=value_mapper,
                reference=0, fill_color=(0.25, 0.41, 0.88, 0.1),
                line_color='transparent', rect_center=0.5, rect_height=1.0)
        container.add(plot)

        # Create the epoch plot
        plot = EpochPlot(source=self.data.epoch, marker='diamond',
                marker_color=(.5, .5, .5, 1.0), marker_height=0.9,
                marker_size=10,
                index_mapper=index_mapper, value_mapper=value_mapper)
        container.add(plot)

        add_default_grids(plot, major_index=1, minor_index=0.25)

        # Hack alert.  Can we separate this out into a separate function?
        if self.parent is not None:
            try:
                self.parent._add_experiment_plots(index_mapper, container)
            except AttributeError:
                pass

        # Create the neural plots
        value_mapper = LinearMapper(range=self.physiology_value_range)
        plot = ExtremesMultiChannelPlot(source=self.data.processed,
                index_mapper=index_mapper, value_mapper=value_mapper)
        self.settings.sync_trait('visible_channels', plot, 'channel_visible', mutual=False)

        overlay = ChannelNumberOverlay(plot=plot)
        self.sync_trait('show_channel_number', overlay, 'visible')
        plot.overlays.append(overlay)

        container.add(plot)
        add_default_grids(plot, major_index=1, minor_index=0.25,
                major_value=1e-3, minor_value=1e-4)
        axis = PlotAxis(component=plot, orientation='left',
                tick_label_formatter=scale_formatter, title='Volts (mV)')
        plot.underlays.append(axis)
        add_time_axis(plot, 'bottom', fraction=True)
        self.physiology_plot = plot

        tool = MultiChannelRangeTool(component=plot)
        plot.tools.append(tool)

        overlay = SpikeOverlay(plot=plot, spikes=self.data.spikes)
        self.sync_trait('visualize_spikes', overlay, 'visible')
        plot.overlays.append(overlay)
        self.spike_overlay = overlay
        
        # Create the threshold overlay plot
        overlay = ThresholdOverlay(plot=plot, visible=False)
        self.sync_trait('visualize_thresholds', overlay, 'visible')
        self.settings.sync_trait('spike_thresholds', overlay, 'sort_thresholds', mutual=False)
        self.settings.sync_trait('spike_signs', overlay, 'sort_signs', mutual=False)
        self.sync_trait('channel_sort', overlay, 'sort_channels', mutual=False)
        plot.overlays.append(overlay)
        self.threshold_overlay = overlay

        self.physiology_container = container